Encoding and decoding an image or image sequence divided into pixel blocks

ABSTRACT

A method and apparatus are provided for coding an image or a sequence of images, generating a data stream including data representative of pixel groups, referred to as blocks, in one of the images. The method includes: grouping blocks in a cluster of blocks according to the proximity of their respective values corresponding to at least one block parameter to be coded; determining a value of the parameter, the value being characteristic of said group of blocks; coding blocks of the cluster, where the values of the blocks for the parameter are coded implicitly by inheritance of the characteristic value or are coded as refinements relative to the characteristic value, and coding a data structure associated with the cluster of blocks, the data structure including data associated with the characteristic value.

CROSS-REFERENCE TO RELATED APPLICATIONS

This Application is a Section 371 National Stage Application ofInternational Application No. PCT/FR2009/050278, filed Feb. 20, 2009 andpublished as WO 2009/112742 on Sep. 17, 2009, not in English.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

None.

THE NAMES OF PARTIES TO A JOINT RESEARCH AGREEMENT

None.

FIELD OF THE DISCLOSURE

The present disclosure relates generally to the field of imageprocessing and more precisely to coding and decoding digital images andsequences of digital images.

BACKGROUND OF THE DISCLOSURE

Digital images and digital image sequences are known to occupy a greatdeal of memory space that, when they are transmitted, makes it necessaryto compress them in order to avoid the problem of congestion in thecommunications network used for that transmission, the usable bit rateof the network generally being limited.

Current compressive coding techniques, notably that of the H.264/MPEG-4AVC (Advanced Video Coding) standard developed by the Joint Video Team(JVT) working group and stemming from the collaboration of the VideoCoding Expert Group (VCEG) of the International Telecommunications Unionand the Moving Picture Expert Group (MPEG) of the ISO/IEC, described inthe document ISO/IEC 14496-10, use techniques of spatial or temporalprediction concerning groups of blocks of pixels referred to asmacroblocks of a current image relative to other macroblocks of the sameimage or a preceding or subsequent image. After such predictive coding,the pixel blocks are processed by applying a discrete cosine transformand then quantized. The coefficients of the quantized pixel blocks arethen scanned in a reading order that makes it possible to take advantageof the large number of zero coefficients at high frequencies, and thenthey are coded entropically.

Those compressive coding techniques are effective, but they are not theoptimum for compressing images featuring regions of homogeneous texture.In the H.264/MPEG-4 AVC standard, spatial prediction of a macroblock inan image relative to another macroblock in the same image is possibleonly if that other macroblock adjoins the macroblock to be predicted incertain predetermined directions relative thereto, generally above andto the left, in a so-called causal vicinity. Similarly, the predictionof the movement vectors of a block or macroblock of an image is a causalprediction relative to the movement vectors of adjoining blocks.

That type of prediction therefore does not make it possible to takeadvantage of the textural similarity of macroblocks of separate areaswith the same texture or of macroblocks that are far apart in an areawith the same texture. In other words, that type of technique does notmake it possible to address simultaneously as a single entity a group ofmacroblocks having common characteristics. Moreover, the movement ofareas of homogeneous texture from one image to another is not takenadvantage of optimally either: the temporal prediction of theH.264/MPEG-4 AVC standard makes it possible to take advantage of themovement of a macroblock from one image to another, but not the factthat the macroblock is part of an area having homogeneous movement.

To solve that problem, so-called regional coding techniques have beenproposed that segment the images of a video sequence in such a manner asto isolate areas of homogeneous texture or movement in the images beforecoding them. Those areas define objects in the images for which a choiceis made to use more refined or less refined coding, for example. Anexample of such a technique is described in the IEEE (Institute ofElectrical and Electronics Engineers) paper published in 2004 entitled“An encoder-decoder texture replacement method with application tocontent-based movie coding” by A. Dumitras et al.

However, those regional coding techniques require sending the decoderthat is the destination of the video sequence a segmentation mapcalculated for each image in the coder that sends the video sequence.The segmentation map is very costly in terms of memory space because itsboundaries generally do not correspond to the boundaries of the blocksof pixels of the segmented images. Moreover, the segmentation of a videosequence into regions of arbitrary shape is not deterministic: theboundaries of the segmentation map generally do not correspond to theboundaries of the real objects that the map attempts to subdivide in theimages of the video sequence. Because of this, only the representationand transmission of such segmentation maps have been standardized (inthe MPEG-4 part 2 standard), not their production.

In conclusion, there are many segmentation techniques and none of themis sufficiently generic for effective segmentation of all kinds of imagesequence. Those complex and non-deterministic techniques have thereforenever been deployed in industrial coders.

SUMMARY

To this end, an embodiment of the invention proposes a method of codingan image or a sequence of images generating a data stream that includesdata representative of pixel groups, referred to as blocks, in one ofsaid images, the method including the steps of:

-   -   grouping blocks in a cluster of blocks according to the        proximity of their respective values corresponding to at least        one block parameter to be coded; and    -   determining a value of said parameter, said value being        characteristic of said group of blocks;

the method being characterized in that it includes the step of:

-   -   coding blocks of said cluster, where the values of said blocks        for said parameter are coded implicitly by inheritance of said        characteristic value or are coded as refinements relative to        said characteristic value, and coding a data structure        associated with said cluster of blocks, said data structure        including data associated with said characteristic value.

By means of an embodiment of the invention, data specific to blocks ofareas of homogeneous texture, color, or movement is pooled in a mannerthat is highly flexible compared to the prior art techniques. Whereappropriate, grouping blocks into clusters of blocks having ahomogeneous texture includes blocks that are far away from one anotheror are parts of separate areas. Moreover, associating a data structurewith each of these clusters also makes it possible to pool block headerdata. Finally, an embodiment of the invention does not requiretransmission of a segmentation map to the coder that is the destinationof the image or images coded by the coding method of an embodiment ofthe invention.

Implicit coding by inheriting a value of a parameter for the blockconcerned means that the inherited value is not coded for that block. Ondecoding, the characteristic value determined for the cluster isassigned to the parameter of the block concerned.

Coding by refining a value of a parameter for a block means that arefinement value for the value concerned is coded for the blockconcerned. On decoding, the value that is assigned to the parameter ofthe block concerned is the characteristic value determined for thecluster plus the refinement value.

According to an advantageous feature, said characteristic valuecorresponds to the value of a block of said cluster for said parameterto be coded.

In one implementation, a particular block of the image is used as a datastructure associated with a cluster of blocks, which makes it possibleto give the cluster the benefit of information on the block, for examplethe temporal prediction used to code the block when it belongs to aninter image.

According to another advantageous feature, in the block grouping step,at least one sub-block of one of the blocks grouped in this way is notassigned to said cluster of blocks, partitioning information for saidblock determining the sub-blocks of said block assigned to said clusterbeing coded in said data structure or in said block during said step ofcoding blocks of said cluster.

This feature makes it possible to define areas of homogeneous texture ormovement precisely: since some sub-blocks are not assigned to thecluster of blocks of which they are part, this cluster in reality groupssub-blocks that define a sharper area than that formed by the blocks ofwhich they are part.

According to another advantageous feature, said cluster of blocks isassociated with priority data for decoding blocks of said clusterrelative to other blocks or clusters of blocks of said image.

This priority data is sometimes useful for specifying to the decoder anorder in which to decode the data associated with the clusters orblocks. For example, if some sub-blocks of a block are not assigned to agroup of which the block is part, it may be preferable to decode thesub-blocks of the block assigned to the cluster first. Even if a clusterof blocks is defined as a cluster of a plurality of clusters, it ispreferable to decode the data structure associated with that clusterfirst, before decoding the data structures associated with the clustersincluded therein.

According to another advantageous feature, when the coding method of anembodiment of the invention is used to code an image sequence, saidcluster of blocks is associated with time-to-live data corresponding toa plurality of successive images of said image sequence, said datastructure associated with said cluster being coded only once for saidsuccessive images.

This time-to-live data makes it possible to pool data common to theclusters from one image to another, which takes advantage of thetemporal dimension of the images to be coded, in addition to theirspatial dimension.

An embodiment of the invention also provides a method of decoding a datastream representative of an image or a sequence of images, said streamincluding data representative of pixel groups, referred to as blocks, inone of said images, the method being characterized in that it includesthe steps of:

-   -   decoding a data structure associated with a set of said blocks        referred to as a cluster of blocks and at least one        characteristic associated value corresponding to a block coding        parameter; and    -   decoding a block of said cluster, assigning to said coding        parameter either said characteristic value if said parameter is        not coded for said block or a refinement value of said        characteristic value calculated from the value corresponding to        said coded parameter if said parameter is coded for said block.

According to an advantageous feature, said step of decoding a block ispreceded by a step of decoding partitioning information for said blockdetermining the sub-blocks of said macroblock assigned to said clusterof blocks, the sub-blocks of said block not assigned to said clusterbeing decoded without using said characteristic value.

An embodiment of the invention further provides a signal carrying a datastream representative of an image or a sequence of images, said streamincluding data representative of pixel groups, referred to as blocks, inone of said images, the signal being characterized in that:

-   -   said stream further includes data representative of a data        structure associated with a set of said blocks referred to as a        cluster of blocks, said structure including data representative        of a characteristic value of said cluster of blocks and        corresponding to a block coding parameter; and    -   the data representative of a block of said cluster either        contains no data representing a value of said coding parameter        or contains data representative of a refinement of said        characteristic value.

An embodiment of the invention further provides a device for coding animage or a sequence of images generating a data stream including datarepresentative of pixel groups, referred to as blocks, in one of saidimages, the device including:

-   -   means for grouping blocks into a cluster of blocks according to        the proximity of their respective values corresponding to at        least one block parameter to be coded; and    -   means for determining a characteristic value of said cluster of        blocks for said parameter to be coded;

the device being characterized in that it includes:

-   -   means for coding a data structure associated with said cluster        of blocks, said data structure including data associated with        said characteristic value; and    -   means for coding blocks of said cluster, including:        -   means for implicitly coding values of said blocks for said            parameter by inheritance of said characteristic value;            and/or        -   means for coding said values as refinements of said            characteristic value.

An embodiment of the invention further provides a device for decoding adata stream representing an image or a sequence of images, said streamincluding data representative of pixel groups, referred to as blocks, inone of said images, the device being characterized in that it includes:

-   -   means for decoding a data structure associated with a set        referred to as a cluster of said blocks and at least one        characteristic value of said cluster of blocks corresponding to        a block coding parameter; and    -   means for decoding a block of said cluster, assigning to said        coding parameter either said characteristic value if said        parameter is not coded for said block or a refinement value of        said characteristic value calculated from the value        corresponding to said coded parameter if said parameter is coded        for said block.

An embodiment of the invention further provides a computer programincluding instructions for executing any of the methods of the inventionwhen it is executed on a computer.

BRIEF DESCRIPTION OF THE DRAWINGS

Other features and advantages become apparent on reading the followingdescription of preferred implementations given with reference to thefollowing figures, in which:

FIG. 1 represents steps of the coding method of an embodiment of theinvention;

FIG. 2 represents a coding device of a first implementation of anembodiment of the invention;

FIG. 3 represents an image coded in accordance with an embodiment of theinvention;

FIG. 4 represents one way of coding macroblocks of an image coded inaccordance with an embodiment of the invention;

FIG. 5 represents another way of coding macroblocks of an image coded inaccordance with an embodiment of the invention;

FIG. 6 represents a decoding device of an embodiment of the invention;

FIG. 7 represents steps of the decoding method of an embodiment of theinvention;

FIG. 8 represents a coding device of a second implementation anembodiment of the invention;

FIG. 9 represents a further way of coding macroblocks of an image codedin accordance with an embodiment of the invention; and

FIG. 10 represents a movement vector associated with the movement of acluster of macroblocks in an image coded in accordance with anembodiment of the invention.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

Three implementations are described below in which the coding method isused to code a sequence of images as a bitstream similar to thatobtained by coding according to the H.264/MPEG-4 AVC standard. In theseimplementations, the coding method is implemented in software orhardware by modifying a coder initially conforming to the H.264/MPEG-4AVC standard, for example. The coding method is represented in the formof an algorithm including steps C1 to C3 represented in FIG. 1 that aregeneric to the three implementations.

Note that the decoding method is symmetrically implemented in softwareor hardware by modifying a decoder initially conforming to theH.264/MPEG-4 AVC standard.

Moreover, as the H.264/MPEG-4 AVC standard subdivides images intomacroblocks of pixels corresponding to blocks of pixel blocks, thecoding method of these implementations group macroblocks into clusters.However, embodiments of the invention can also be used to code or decodean isolated image or any image sequence made up of blocks of pixels.Thus embodiments of the invention can equally be implemented, forexample, by modifying a video coder initially conforming the SVC(Scalable Video Coding) standard, which is an extension of theH.264/MPEG-4 AVC standard currently in process of standardization by theJoint Video Team (JVT).

In a first implementation, the coding method of an embodiment of theinvention is implemented in a coding device CO1 represented in FIG. 2.

The first step C1 represented in FIG. 1 groups macroblocks of an imageIE from the image sequence to be coded into one or more clusters ofmacroblocks. For this the image IE is applied to the input of a moduleMRG1 for grouping macroblocks into clusters shown in FIG. 2.

This cluster grouping module MRG1 uses, for example, a regional growthmethod known as the k-means clustering method, which uses an algorithmthat segments a set of elements into classes of elements by measuringthe distance between the features of the elements of the set to besegmented. Such a method is described in the IEEE paper by T. Kanungo etal. published in 2002 entitled “An Efficient k-means ClusteringAlgorithm: Analysis and Implementation”. The cluster grouping moduleMRG1 thus pre-analyzes the images of the image sequence to be codedbefore transmitting them, with information defining the clusters ofmacroblocks defined for each image from the sequence, to the movementestimation module MEV1, the prediction calculation module MCP1, and thedecision module MDC1. The operation of these modules is described indetail below.

Thus in this step C1 the macroblocks of the image IE are grouped intoclusters as a function of the similarity of the orientations of theirtextures, defined in terms of texture contours and gradients, or as afunction of the similarity of their colors. Three clusters G1, G2, andG3 are determined in this way, as shown in FIG. 3. The cluster G1comprises macroblocks with very similar texture and movement, thecluster G2 comprises macroblocks with similar orientations (i.e. thecontours that pass through these macroblocks comply with a certainorientation or the texture of these macroblocks is globally oriented ina particular direction) and the cluster G3 groups macroblocks ofhomogeneous texture.

Note that some blocks of macroblocks of the cluster G2 are not assignedto the cluster G2, which sharpens part of the contour of the cluster G2.

Moreover, in this first implementation, as in the second implementationdescribed below, only texture data is pooled via macroblock clusterdata. The third implementation described below is an example of using anembodiment of the invention to pool movement data between macroblocks ofa homogeneous movement cluster.

In the next step C2 one or more characteristic values of each of theclusters G1, G2, and G3 determined in the step C1 are determined by thecluster grouping module MRG1, which assigns characteristic texturevalues to the clusters G1 and G3 and a characteristic textureorientation value to the cluster G2. The texture orientation valueassigned to the cluster G2 is, for example, the mean value of theorientations of the contours of each of the macroblocks of the clusterG2. Similarly, the texture values assigned to the clusters G1 and G3are, for example, the respective mean values of the macroblocks of thecluster G1 and the cluster G3, respectively.

Note that, if a cluster allows it, the module MRG1 may determine aplurality of characteristic values for that cluster. Such a cluster istherefore associated with an mean pixel value and a texture orientationvalue, for example. It is possible to code a texture in various ways,for example an add-on complementing existing methods in a H.264/MPEG-4AVC coder:

-   -   it is coded in the form of an orientation associated with a        color, these two data items making it possible to resynthesize        the texture; or    -   it is coded directly in the form of a square of pixels; or    -   only statistical texture values (mean, variance, etc.) are        stored, in order to regenerate it in an entirely parametric        manner.

The choice between these forms of coding depends on their cost in termsof bit rate, for example.

Note that the term “value” is employed here in the sense of “value of aparameter” and therefore may designate a plurality of values as afunction of that parameter. In this implementation, for macroblockcoding parameters other than those present in the headers of themacroblock data, see those defined in the H.264/MPEG-4 AVC standard, forexample. As a function of the coding option chosen, a macroblock texturevalue corresponds to three squares or matrices of values, for example,i.e. a luminance value square and two chrominance value squares.

At the end of the step C2, the cluster grouping module MRG1 transmitsthe image IE and the information defining the clusters G1, G2, and G3 tothe prediction calculation module MCP1 and the decision module MDC1. Theinformation defining one of the clusters G1, G2, or G3 is as follows:

-   -   the index of the macroblocks grouped in this cluster;    -   the characteristic value or values assigned to this cluster in        the step C2, such as a characteristic texture orientation value;    -   for each macroblock of this cluster for which one or more blocks        or sub-blocks are not assigned to the cluster, partitioning        information defining the blocks and sub-blocks of the macroblock        that are assigned to this cluster;    -   if this cluster is present in a plurality of consecutive images,        where appropriate cluster time-to-live data, for example equal        to the remaining number of images with which the cluster is        concerned, as well as data for updating the index of the        macroblocks of this cluster relative to the preceding image,        where appropriate partitioning information associated with the        updated macroblocks, if these macroblocks contain blocks or        sub-blocks not assigned to this cluster, and information for        updating characteristic values of the cluster relative to those        assigned to it in a preceding image;    -   decoding priority data if the cluster must be decoded before or        after other clusters of macroblocks, or before or after the        macroblocks that are not assigned to clusters, referred to as        “free” macroblocks.

The next step C3 codes the characteristic values determined in the stepC2 in data structures associated with each of the clusters G1, G2, andG3 and codes the macroblocks of the image IE.

When coding a cluster, if a time-to-live is associated with it, theprediction calculation module MCP1 where appropriate calculates thedifference between the characteristic values assigned to the cluster inthe step C2 for the image IE and the characteristic values assigned tothe cluster in the step C2 for the preceding image. Thus onlycharacteristic value temporal prediction residues (updating information)are coded from one image to another for this cluster, except for thefirst image in which this cluster appears, of course. Alternatively, ifa time-to-live is associated with the cluster, no characteristic valueis coded for the images following the first image in which this clusterappears (there is no updating of characteristic values). In thisvariant, the decoder always re-uses the same characteristic values ofthe cluster, i.e. those received for the first image in which thecluster appears.

The decision module MDC1 codes the characteristic values of a cluster orthe predictions of those characteristic values in a similar manner tocoding the corresponding values of an H.264/MPEG-4 AVC formatmacroblock.

FIG. 4 shows a slice T of macroblocks of the image IE coded inaccordance with a variant of the invention. Compared to the H.264/MPEG-4AVC format, a field GD coding data specific to the clusters ofmacroblocks of the slice is inserted between the slice header data fieldSH and the macroblock data field SD.

This field GD codes the data structures associated with each cluster inwhich the characteristic values of these clusters are coded. In thisimplementation, their syntax is similar to the H.264 syntax. Thus thedata structure associated with the cluster G1 comprises data G1D andpointers P11, P12, and P13 each of which points to a macroblock of thecluster G1. The data G1D comprises:

-   -   a field GT specifying a type of coding for the cluster, for        example intra coding or inter coding;    -   a field GP indicating the type of prediction used to code the        characteristic values of the cluster (no prediction or the        position of the prediction values); and    -   a field GM containing the coding of the characteristic value or        values of the group, where applicable predicted, and possibly a        time-to-live associated with the cluster, decoding priority        data.

The time-to-live associated with a cluster is alternatively codedimplicitly, for example if that time-to-live is equal to the duration ofa group of pictures (GOP).

The field GD also contains the data of the clusters G2 and G3, the dataof the cluster G3 being represented in FIG. 4 by a data field G3Dfollowed by pointers P31, P32, P33, and P34 pointing to the macroblocksof the cluster G3.

When a pointer relates to a macroblock of which only some blocks are notassigned to a cluster, for example one of the pointers of the clusterG2, this pointer is coded in a data structure including macroblockpartitioning data. This partitioning data is explained below.

Note that the slice T generally corresponds to the entire image IE. Forexample, if the macroblock slices used each contain only part of theimage IE, an FMO (Flexible Macroblock Ordering) mechanism is used togroup the data of a cluster and the data of macroblocks associated withthat cluster in the same macroblock slice.

FIG. 5 shows the macroblock slice T coded by another variant of theinvention. Compared to the FIG. 4 variant, the data G1D further includesa cluster index field GI and the data structures associated with each ofthe clusters do not contain pointers to the macroblocks of thoseclusters. That a macroblock belongs to a cluster is indicated otherwise,using a coded field ML in each macroblock that includes one or morecluster indices, as described in detail below with reference to themacroblock coding step C3. Because of this, in this coding variant thecluster data GD for a given cluster does not contain data for updatingmacroblocks grouped in the cluster or decoding priority data.

Note that these two coding variants make it possible for the samemacroblock to be part of a plurality of clusters. Accordingly, thismacroblock inherits, for example, a characteristic value from a firstcluster and another characteristic value from another cluster.

Moreover, the priority data associated with some clusters makes itpossible to “connect” those clusters: for example, if characteristicvalues of one cluster are used to predict characteristic values ofanother cluster, the priority data is used to indicate to the decoderthat it is necessary to decode the reference cluster first and then theother cluster predicted from that reference cluster.

The macroblocks of the image IE are also coded in this step C3. As underthe H.264/MPEG-4 AVC standard, the prediction calculation module MCP1calculates various possible predictions of the macroblocks of the imageIE. These predictions are calculated from the image IE or from otherimages of the sequence previously coded and then decoded and insertedinto a list of reference images IR1. These reference images IR1 areconstructed from the initial images of the image sequence to be coded inaccordance with the H.264/MPEG-4 AVC standard:

-   -   discrete cosine transform and quantization coding is effected by        the transform and quantization module MTQ1;    -   inverse discrete cosine transform and inverse quantization        decoding is then effected by the inverse quantization and        transform module MTQI1; and    -   finally, a block effect filter module MFB1 reduces block effects        in images coded in this way and decoded to provide at the output        the reference images IR1.

The predictions calculated by the prediction calculation module MCP1depend on which type of image the image IE is:

-   -   if the image IE is an intra image, i.e. one coded without        temporal prediction relative to macroblocks of other senders of        the sequence to be coded, the prediction calculation module MCP1        calculates possible spatial predictions of each macroblock of        the image IE relative to other macroblocks of the image IE; and    -   if the image IE is an inter image, i.e. one for which it is        possible to code a macroblock by temporal prediction relative to        macroblocks of other images from the sequence to be coded, then        the module MEV1 calculates movements between the image IE and        one or more reference images IR1. The prediction calculation        module MCP1 then calculates possible temporal predictions of        each macroblock of the image IE relative to macroblocks of other        images from the sequence to be coded and also possible spatial        predictions of each macroblock of the image IE relative to other        macroblocks of the image IE.

In addition to the temporal and spatial predictions provided for by theH.264/MPEG-4 AVC standard, the prediction calculation module MCP1calculates for the macroblocks of the image IE in a cluster thedifferences between the characteristic values of that cluster and thecorresponding values of those macroblocks.

Once the prediction calculation module MCP1 has calculated the possiblepredictions, the decision module MDC1 scans the macroblocks of the imageIE and, in this step C3, chooses the type of prediction used to codeeach of these macroblocks. From the possible predictions for amacroblock, the decision module MDC1 chooses either the optimumprediction according to a bit rate vs. distortion criterion or not touse any prediction if the bit rate vs. distortion criterion for the “noprediction” option is better than all possible predictions. A usable bitrate vs. distortion criterion is described in the IEEE paper by T.Wiegang et al. published in July 2003 entitled “Rate-Constrained CoderControl and Comparison of Video Coding Standards”.

If the macroblock scanned by the decision module MDC1 is a freemacroblock, i.e. does not belong to any cluster, the decision moduleMDC1 codes that macroblock according to a spatial or temporal predictionor with no prediction, depending on the type (inter or intra) of theimage IE and possible optimization of the bit rate vs. distortioncriterion.

In contrast, if the macroblock scanned by the decision module MDC1 is amacroblock of a cluster, the decision module MDC1 codes that macroblockeither using the data of that cluster or in the same way as for a freemacroblock, as a function of the choice that optimizes the bit rate vs.distortion criterion.

Note that when a macroblock of a cluster is coded like a freemacroblock, in the FIG. 4 coding variant the data of that clustercontains no pointer to the macroblock. This is why cluster data is codedat the same time as coding macroblocks of the cluster. In other words,syntax production of the slice T takes place after all the codingchoices for that slice have been finalized, for both cluster data andfor macroblock data.

The macroblocks of the image IE are coded in macroblock slices inaccordance with one of the variants represented in FIGS. 4 and 5. Forthe slice T, for example, each macroblock is coded in a field MDi of thefields MD1 to MDn in the field SD reserved for macroblock data. Thefield SKR represents a macroblock coded in accordance with the skip_runmode of the H.264/MPEG-4 AVC standard.

In the FIG. 4 variant, free macroblocks are coded as in the H.264/MPEG-4AVC standard: each includes a field MT specifying the type (inter orintra) of the macroblock concerned, a field MP indicating the predictiondirection used (spatial for intra macroblocks, movement vectors forinter macroblocks), and a field MCR coding the values of the macroblockresidues. In contrast, for a macroblock of a cluster:

-   -   the field MT is not present;    -   the field MP is present to indicate the mode of prediction of        the values of the corresponding macroblock corresponding to        parameters other than those corresponding to the characteristic        values of the cluster; and    -   the field MCR is present if a residue is coded to refine the        data inherited from the cluster.

In the FIG. 5 variant, free macroblocks are also coded as in theH.264/MPEG-4 AVC standard, but the macroblocks of a cluster have a newmacroblock type, for example MB_CLUSTER, coded in the field MT andindicating that they belong to a cluster. If a macroblock is of theMB_CLUSTER type, it also has a new header field ML including one or morecluster indices to indicate the cluster or clusters of which it is part.

Other coding variants may of course be envisaged. For example, inanother coding variant, macroblocks are coded in the same way as in theFIG. 5 variant except that the header field ML is a simple flag havingthe value 0 or 1 according to whether the macroblocks are in a clusteror not. Note nevertheless that this other variant does not make itpossible for a macroblock to be part of a plurality of clusters.

Moreover, in these variants, the field MCR of a macroblock using thedata of a cluster is coded as follows:

-   -   the values of the coding parameters of the macroblock that do        not have corresponding values in the data of the cluster to        which it belongs are coded in a similar manner to AVC coding        using the prediction mode indicated in the field MP; and    -   the values of the coding parameters of the macroblock that do        have corresponding values in the data of the cluster to which it        belongs are not coded, or only the differences between the        characteristic values of the cluster and the corresponding        values of the macroblock are coded; for example, the choice        between coding nothing for these values or coding only        refinement values is made according to a bit rate vs. distortion        criterion between these characteristic values and the        corresponding values of the macroblock.

Thus the frame T includes macroblocks some parameter values of which arenot coded explicitly but implicitly by inheriting characteristic valuescoded in the cluster data GD.

If only some blocks of a macroblock are not part of a cluster, thepositioning information associated with the macroblock indicates thesubdivision of the macroblock, making it possible to determine whichblocks are assigned to the cluster, the other blocks, thereafterreferred to as “free” blocks, not being assigned to it. For example, inthe FIG. 5 variant, this subdivision is coded by a flag associated witheach block of the macroblock and indicating whether the block is free ornot. Blocks assigned to the cluster are coded in a similar manner tocoding a macroblock entirely assigned to the cluster, i.e. for theparameters corresponding to the characteristic values of the cluster thevalues of these blocks inherit or refine these characteristic values.The partitioning information indicates for each free block the AVCprediction type used. Moreover, the default vicinity used to determineprediction directions is modified, with the result that the free blocksdo not use the blocks of the macroblock that are part of the cluster.

When this structural coding has been effected by the decision moduleMDC1, any residue coefficients that correspond to the blocks of theimage IE are sent to the transform and quantization module MTQ1 thatapplies a discrete cosine transform followed by quantization. Themacroblock slices with these quantized coefficients are then sent to theentropic coding module MCE1 to produce, with other images of the videosequence already coded in the same way as the image IE, a videobitstream F1 coded in accordance with an embodiment of the invention.

The bitstream F1 coded in this way is sent via a communications networkto a remote terminal that includes a decoder DEC represented in FIG. 6.

The bitstream F1 is first sent to the entropic decoder module MDE, whicheffects decoding that is the inverse of the coding effected by themodule MCE1. For each image block to be reconstructed, any coefficientsdecoded by the module MDE are sent to the inverse quantization andinverse transform module MQTI.

In the step C3 of coding in accordance with an embodiment of theinvention, the image reconstruction module MRI then receives decodeddata corresponding to the data produced by the module MDC1, ignoringtransmission errors. The module MRI executes the steps D1 and D2 of thedecoding method represented in FIG. 7. Symmetrically relative to thecoding method, these steps are generic to the three implementations.

The first step D1 decodes data structures of clusters coded in themacroblock slices of the image IE. The module MRI verifies by means ofthe header field GP of the data of a given cluster whether or not atemporal prediction was used to code the data of that cluster.

If a prediction has been used relative to a preceding image of thestream F1 or part of the current image, the module MRI uses predictionvalues supplied by the prediction calculation module MCP shown in FIG. 6to decode the characteristic values of the cluster. The module MCPreceives:

-   -   reference images IR from the image sequence to be decoded        corresponding to images from the sequence previously        reconstructed by the reconstruction module MRI and filtered by        the module MFB to reduce block effects caused by decoding; and    -   the characteristic values of the clusters previously decoded and        held in its memory by the reconstruction module MRI.

The prediction values for each characteristic value of the cluster arethen added to the values decoded by the module MQTI.

If the field GP of the cluster does not indicate temporal prediction,the values decoded by the module MQTI are used as they stand ascharacteristic values of the cluster.

Once the characteristic values of each cluster of the image IE have beendecoded, if the image IE was coded according to the FIG. 4 variant, themodule MRI draws up for each cluster of the image IE a list of themacroblocks associated with that cluster and where applicable of theblocks individually assigned to that cluster if some blocks arepartitioned.

As explained with reference to the coding method, some clusters having atime-to-live spanning a plurality of images and coded in accordance withthe FIG. 4 coding variant contain data for updating the macroblocks ofeach of these clusters. In this situation the module MRI draws up a listof macroblocks associated with such a cluster, applying the updatingdata included in this cluster to a list drawn up for the preceding imageand held in a memory of the module MRI.

When the lists of macroblocks and blocks of the clusters of the image IEhave been drawn up, if the data associated with those clusters containsdecoding priority data indicating a decoding priority of one clusterrelative to another cluster or to the free macroblocks of the image IE,the module MRI determines an order of decoding the macroblocks andblocks as a function of that priority data.

In contrast, if the image IE was coded using the FIG. 5 variant, themodule MRI does not draw up lists of macroblocks for each cluster. Thesystem of attaching a macroblock to a cluster by a field ML contained inthe header data of the macroblock enables the module MRI to take accountof this attachment when scanning the image IE to decode the macroblockssuccessively.

If a decoding order is established by the module MRI in the step D1, themodule MRI decodes the macroblocks of the image IE in that order in thestep D2; if not, decoding is effected in the usual order for scanningthe macroblocks of the image IE.

The free macroblocks of the image IE are decoded in the conventional wayusing the temporal or spatial prediction indicated in the macroblockheader fields MP.

A macroblock or block that is part of a cluster of the image IE isdecoded as follows:

-   -   for a parameter to be decoded that corresponds to a        characteristic value of the cluster:        -   if the data of the macroblock or block contains no value            corresponding to the parameter to be decoded, the module MRI            assigns this parameter the characteristic value of the            cluster;        -   if the data of the macroblock or block contains a value            corresponding to the parameter to be decoded, the module MRI            uses that value to refine the characteristic value of the            cluster, for example by adding that value to the            characteristic value of the cluster, and assigns the value            calculated in this way to the parameter;    -   for a parameter to be decoded that does not correspond to a        characteristic value of the cluster, the corresponding value        contained in the data of the macroblock or block is decoded        using the AVC prediction indicated for that block or macroblock.

When a macroblock is part of a plurality of clusters, the module MRIfirst verifies whether partitioning information is coded for thatmacroblock, indicating, for each of these clusters, which blocks orsub-blocks of the macroblock are assigned to it. If such informationexists, the blocks and sub-blocks assigned to a single cluster aredecoded as described above for decoding a macroblock that is part ofonly one cluster.

If such information is not coded for this macroblock or if some blocksor sub-blocks of the macroblock are assigned to a plurality of clusters,the module MRI examines for them, one macroblock coding parameter at atime, to which parameters it is possible to assign by inheritance acharacteristic value of one of these clusters or a refinement of thatcharacteristic value, as described above for decoding a macroblock thatis part of only one cluster. When it is possible to assign to a codingparameter by inheritance a plurality of characteristic values ofdifferent clusters or a plurality of refinements of characteristicvalues of different clusters, the module MRI assigns that parameter acombination of these characteristic values or a refinement of thatcombination, for example, or if there is priority data for the variousclusters the module MRI assigns to this coding parameter by inheritancethe characteristic value of the highest priority cluster or a refinementof that characteristic value.

When all the macroblocks of the image IE have been decoded, the imagereconstruction module MRI supplies at the output of the decoder DEC adecoded image ID corresponding to the image IE.

The coding method of the second implementation is implemented in acoding device CO2 shown in FIG. 8. The steps of the coding method of thesecond implementation are the same as in FIG. 1 but are implementeddifferently, the macroblocks of the image IE being grouped into clusterswhile coding the “free” macroblocks of the image IE, i.e. those not yetgrouped.

Note that this second implementation is described in less detail thanthe first implementation because it has many elements in common with thefirst implementation.

In this second implementation, the image IE to be coded arrives directlyat the input of a movement estimation module MEV2, a predictioncalculation module MCP2, and a decision module MDC2. As in the firstimplementation, the prediction calculation module MCP2 calculatespossible predictions of the macroblocks of the image IE from the imageIE or from reference images IR2 constructed from other images of thesequence previously coded by the transform and quantization module MTQ2,decoded by the inverse transform and quantization module MTQI2, and thenfiltered by the block effect filter module MFB2. These modules MTQ2,MTQI2, and MFB2 function like the modules MTQ1, MTQI1, and MFB1,respectively, of the device CO1.

The predictions calculated by the prediction calculation module MCP2depend on the type (intra or inter) of image IE:

-   -   If the image IE is an intra image, the prediction module MCP2        calculates possible spatial predictions for each macroblock of        the image IE relative to other macroblocks of the image IE.    -   If the image IE is an inter image, the module MEV2 calculates        the movements between the image IE and one or more reference        images IR2. The prediction calculation module MCP2 then        calculates possible temporal predictions for each macroblock of        the image IE relative to macroblocks of other images of the        sequence to be coded and possible spatial predictions for each        macroblock of the image IE relative to other macroblocks of the        image IE.

Once these predictions have been calculated, the decision module MDC2then executes the steps C1 to C3 of the coding method shown in FIG. 1.

The step C1 groups macroblocks of the image IE into clusters. This stepuses predictions previously calculated for the macroblocks of the imageIE by the module MCP2 that make it possible to determine arepresentative macroblock for a plurality of other macroblocks that arethen grouped in a cluster. In contrast to the first implementation, thisrepresentative macroblock is determined using the bit rate vs.distortion criterion and therefore not necessarily using a perceptualcriterion.

The next step C2 determines characteristic values of the clusters formedin the step C1. The characteristic values for a given cluster correspondto the coding parameter values of the representative macroblock of thecluster.

The next step C3 codes the characteristic values determined in this wayin data structure(s), a data structure being associated with eachcluster formed in the step C1, and codes the macroblocks of the clustersformed in the step C1. A cluster is defined by the followinginformation:

-   -   the index of the macroblocks grouped in the cluster;    -   the index of the representative macroblock of the cluster;    -   for each macroblock of the cluster for which one or more blocks        or sub-blocks are not assigned to the cluster, partitioning        information defining the blocks and sub-blocks of the macroblock        assigned to the cluster;    -   where applicable, if the cluster is present in a plurality of        consecutive images, cluster time-to-live data equal for example        to the number of subsequent images to which the cluster still        pertains, data for updating the index of the macroblocks of the        cluster relative to the preceding image, and where applicable,        if these macroblocks contain blocks or sub-blocks not assigned        to the cluster, partitioning information associated with the        updated macroblocks;    -   if the cluster must be decoded before or after other clusters of        macroblocks or before or after the free macroblocks, decoding        priority data.

In this second implementation, the characteristic values of the clusterare coded with reference to the representative macroblock of the clusteras shown in FIG. 9.

Compared to the FIGS. 4 and 5 coding variants, there is no cluster datafield GD. In this implementation the data structure coding thecharacteristic values of the cluster is the representative macroblock ofthe cluster. All other cluster data is contained in the macroblock data.

As in the FIGS. 4 and 5 coding variants, the free macroblocks are codedto the H.264/MPEG-4 AVC standard, i.e. each contains a field MTspecifying the type (inter or intra) of the macroblock concerned, afield MP indicating the prediction direction used, and a field MCRcoding the macroblock residue values or the macroblock non-predictedvalues if no temporal or spatial prediction is used for the macroblockconcerned.

In contrast, the macroblocks coded using the characteristic values of acluster and the representative macroblock of the cluster each includethe following fields:

-   -   a field MT that codes a new macroblock type MB_CLUSTER,        indicating that the macroblock concerned is part of a cluster;    -   a field MZ that indicates if the macroblock concerned is the        representative macroblock of the cluster or not, gives a cluster        index, and where applicable gives a time-to-live of the cluster        and a decoding priority for the cluster;    -   a field MP, present only if the macroblock concerned is the        representative macroblock of the cluster, that indicates the        prediction used to code the representative macroblock        (prediction type and where applicable prediction direction); and    -   where applicable, a field MCR coding the prediction residue of        the macroblock concerned.

A representative macroblock of a cluster is thus coded according to aprediction as defined in the H.264/MPEG-4 AVC standard, for example aspatial or temporal prediction. Its field MCR codes the predicted valuesof the macroblock or the non-predicted values if no temporal or spatialprediction is used for the macroblock concerned.

The other macroblocks that are parts of clusters are coded either usingthe data of those clusters or in the same way as a free macroblock, as afunction of the choice that optimizes the bit rate vs. distortioncriterion.

When the module MDC2 uses the data of a cluster to code a macroblock, ituses the initial, i.e. non-predicted, values of the representativemacroblock of the cluster to code the field MCR of the macroblock. To bemore precise, the value of a parameter contained in this field MCR iseither not coded or equal to the difference between the correspondinginitial value of the representative macroblock of the cluster and thecorresponding initial value of the macroblock to be coded. If this valueis not coded, it is in fact coded implicitly by inheriting thecorresponding initial value from the representative macroblock of thecluster.

Once the decision module MDC2 has effected this structural coding, thecoefficients corresponding to the blocks of the image IE are sent to thetransform and quantization module MTQ2 that applies a discrete cosinetransform followed by quantization. The macroblock slices with thesequantized coefficients are then sent to the entropic coding module MCE2to produce, with the other images of the video sequence already coded inthe same way as the image IE, a video bitstream F2 coded in accordancewith an embodiment of the invention.

The bitstream F2 coded in this way is sent to a remote terminal via acommunications network. This terminal includes a decoder of anembodiment of the invention that has the same structure as the decoderDEC of the first implementation, but compared to that decoder DEC itsimage reconstruction module functions differently, as it effectsdecoding corresponding to coding that is the inverse of that effected bythe module MDC2. This decoding is effected in the two decoding steps D1and D2 shown in FIG. 7.

In the step D1 the image reconstruction module decodes data structuresof clusters coded in the slices of macroblocks of the image IE. Theimage reconstruction module scans the macroblocks contained in thestream F2 to identify the representative macroblocks of the clusters,each of these representative macroblocks identifying a cluster. Duringthis scanning it also identifies macroblocks coded using data from theclusters and decodes the fields MZ associated with the macroblocks ofthe clusters in order to determine a decoding order, where applicabletaking account of any priority data included in the fields MZ.

If temporal or spatial prediction is indicated in the field MP of therepresentative macroblock, in this step D1 the image reconstructionmodule also decodes each representative macroblock of a clusterpreviously identified, where applicable using prediction data calculatedwhile coding preceding images.

The values contained in the fields MCR of these representativemacroblocks serve as references for subsequent decoding of the otherMB_CLUSTER macroblocks.

In the step D2 the image reconstruction module decodes other macroblocksof the stream F2 in the decoding order established in the step D1.

The macroblocks of the stream F2 having a field MT indicating an intraor inter macroblock are decoded in the conventional way using the typeof prediction indicated in the macroblock header fields MP.

A macroblock of a cluster that is not the representative macroblock ofthe cluster, having its field MT equal to MB_CLUSTER, is decoded in thefollowing manner:

-   -   if the data in the field MCR of the macroblock contains no value        corresponding to the parameter to be decoded, the image        reconstruction module assigns this parameter the corresponding        previously decoded value of the representative macroblock of the        structure;    -   if the data in the field MCR of the macroblock contains a value        corresponding to this parameter to be decoded, the image        reconstruction module uses this value to calculate a refinement        of the corresponding previously decoded value of the macroblock        representative of the cluster and assigns the value calculated        in this way to the parameter.

The coding method of a third implementation is implemented in a codingdevice similar to the device CO1 from FIG. 2 but in which the clustergrouping module detects homogenous movement of macroblocks of the imageIE relative to a preceding image, for example movement of the clusterG1. This homogeneous movement of macroblocks is either modeled by thecluster grouping module using a vector V shown in FIG. 10 or codedotherwise than by a single vector, for example parametrically.

In this third implementation, using data from the cluster G1, it ismovement data that is pooled, not texture data. Moreover, the codingmethod of this third implementation comprises the same steps as shown inFIG. 1 and is therefore described in less detail than in the firstimplementation, as these steps have many elements in common with thefirst implementation.

In the first step C1, the cluster grouping module groups into clusterssets of macroblocks having a homogeneous movement, here the macroblocksof the cluster C1, using movement estimation techniques similar to thoseused by the movement estimation module MEV1.

The next step C2 determines one or more movement characteristic valuesof the cluster G1. Here the cluster grouping module averages themovement vectors associated with the movements of the macroblocks of thecluster G1 from the image IP to the image IE, resulting in a movementcharacteristic vector V.

At the end of the step C2, the cluster grouping module sends the imageIE and the information defining the cluster G1 to the predictioncalculation and decision modules of the coder used in this thirdimplementation. The information defining the cluster G1 consists of:

-   -   the index of the macroblocks grouped in this cluster; and    -   the values of the movement characteristic vector V corresponding        to two AVC type parameters for coding a movement vector.

Alternatively, as in the first and second implementations, the clusterG1 is assigned a time-to-live, or decoding priority data or partitioninginformation if some blocks of a macroblock of the cluster G1 are notassigned to the cluster G1. In this variant, a temporal prediction forcoding the movement characteristic vector of the cluster G1 maytherefore be envisaged.

In the next step C3 the decision module codes the characteristic vectorV of the cluster G1 in a data structure associated with the cluster G1and codes the macroblocks of the image IE in a similar way to coding anymovement vector of a macroblock in the H.264/MPEG-4 AVC format.

The data from the cluster G1 and the macroblocks of the image IE arecoded in a similar way to either the FIG. 4 or the FIG. 5 variant.

In the FIG. 4 variant in particular, the data structure associated withthe cluster G1 comprises data G1D and pointers P11, P12, and P13 each ofwhich points to a macroblock of the cluster G1, and the data G1Dincludes a field GM containing the coded movement characteristic vectorV of the cluster. In the FIG. 5 variant, the data G1D further includes acluster index field G1 and the data structures associated with each ofthe clusters contain no pointers to the macroblocks of the clusters, thefact that a macroblock is part of a cluster being indicated otherwise,by using a coded field ML in each macroblock.

According to a bit rate vs. distortion criterion, the decision modulecodes the free macroblocks of the image IE using the most pertinent AVCprediction and the macroblocks of the cluster G1 either as freemacroblocks or using the data associated with the cluster G1.

Under such circumstances, when the FIG. 4 coding variant is used, amacroblock of the cluster G1 includes only one field, namely the fieldMCR, which is present when a residue is coded to refine the movementcharacteristic vector V of the cluster or where a residue is coded torefine the texture of the macroblock relative to its texture obtained bymovement compensation using the characteristic vector V, possiblyrefined.

In contrast, if the FIG. 5 variant is used, this macroblock includes thefollowing fields:

-   -   a field MT corresponding to a new type of macroblock, for        example MB_CLUSTER, indicating that it is part of a cluster;    -   a new header field ML, which indicates the cluster of which the        macroblock is part; and    -   a field MCR that is present if a residue is coded to refine the        movement characteristic vector V of the cluster or if a residue        is coded to refine the texture of the macroblock relative to the        texture obtained by movement compensation using the        characteristic vector V, possibly refined.

Note that a macroblock of the MB_CLUSTER type has no field MP becausethis implementation does not use temporal prediction for coding thecluster data.

In each of these variants, the field MCR of a macroblock using data fromthe cluster G1 is coded as follows:

-   -   the value of the movement vector calculated beforehand for this        macroblock by the movement estimation module of the coder is not        coded or only the difference between that value and the value of        the movement characteristic vector V of the cluster is coded;        and    -   the values of the other coding parameters of the macroblock, for        example characterizing its texture, are not coded or only the        difference between the corresponding values obtained by movement        compensation using the movement vector of the macroblock        calculated beforehand by the movement estimation module are        coded.

In FIG. 10, for example, if the macroblock MB is considered tocorrespond more or less to the macroblock MA of the preceding image IPand the movement vector between the macroblock MB and the macroblock MAcorresponds to the movement characteristic vector V of the cluster, thenthe field MCR of the macroblock MB:

-   -   does not contain a value corresponding to the movement vector        parameter, that value being coded implicitly as equal to the        value of the movement characteristic vector V of the cluster;        and    -   does contain texture residue values corresponding to texture        differences between the macroblock MB and the macroblock MA.

Once this structural coding has been effected by the decision module,discrete cosine transform and then quantization are then applied to anyresidue coefficients corresponding to the blocks of the image IE. Theslices of macroblocks with quantized coefficients then undergo entropiccoding to produce a video bitstream coded in accordance with anembodiment of the invention.

This video bitstream is then decoded by a decoder of an embodiment ofthe invention effecting operations that are the inverse of thoseeffected by the coder and in a similar manner to the decoding methodsdescribed above for the other implementations of the invention.

Note that other implementations and other coding and decoding variantsfor implementing the coding method and the decoding method of theinvention may be envisaged. Moreover, diverse coding syntaxes arepossible. For example, data from clusters having similar characteristicvalues is pooled in a data structure that is associated with theclusters and is used to decode data structures individually associatedwith each of these clusters.

An exemplary embodiment aims to solve the drawbacks of the prior art byproviding image coding and decoding methods and devices in which dataspecific to each block or macroblock, such as texture or color data, ispooled between blocks or macroblocks having a similar texture or color.

Thus the advantages of pooling information in regional coding methodsare obtained without the drawback of fine segmentation requiring thetransmission of a segmentation map.

Although the present disclosure has been described with reference to oneor more examples, workers skilled in the art will recognize that changesmay be made in form and detail without departing from the scope of thedisclosure and/or the appended claims.

1. A method of coding an image or a sequence of images generating a datastream that include data representative of pixel groups, referred to asblocks, in one of said images, the method including the steps of:grouping blocks in a cluster of blocks according to proximity of theirrespective values corresponding to at least one block parameter to becoded; determining a value of said parameter, said value beingcharacteristic of said group of blocks; and coding blocks of saidcluster, where the values of said blocks for said parameter are codedimplicitly by inheritance of said characteristic value or are coded asrefinements relative to said characteristic value, and coding a datastructure associated with said cluster of blocks, said data structureincluding data associated with said characteristic value.
 2. The codingmethod according to claim 1, wherein said characteristic valuecorresponds to the value of a block of said cluster for said parameterto be coded.
 3. The coding method according to claim 1, wherein in theblock grouping step at least one sub-block of one of the blocks groupedin this way is not assigned to said cluster of blocks, partitioninginformation for said block determining the sub-blocks of said blockassigned to said cluster being coded in said data structure or in saidblock during said step of coding blocks of said cluster.
 4. The codingmethod according to claim 1, wherein said cluster of blocks isassociated with priority data for decoding blocks of said clusterrelative to other blocks or clusters of blocks of said image.
 5. Themethod of coding a sequence of images according to claim 1, wherein saidcluster of blocks is associated with time-to-live data corresponding toa plurality of successive images of said image sequence, said datastructure associated with said cluster being coded only once for saidsuccessive images.
 6. A method of decoding a data stream representativeof an image or a sequence of images, said stream including datarepresentative of pixel groups, referred to as blocks, in one of saidimages, the method comprising the steps of: decoding a data structureassociated with a set of said blocks referred to as a cluster of blocksand at least one characteristic associated value corresponding to ablock coding parameter; and decoding a block of said cluster, assigningto said coding parameter either said characteristic value if saidparameter is not coded for said block or a refinement value of saidcharacteristic value calculated from the value corresponding to saidcoded parameter if said parameter is coded for said block.
 7. Thedecoding method according to claim 6, wherein said step of decoding ablock is preceded by a step of decoding partitioning information forsaid block determining the sub-blocks of said block assigned to saidcluster of blocks and during said step of decoding said block thesub-blocks of said block not assigned to said cluster are decodedwithout using said characteristic value.
 8. A method comprising:generating with a device a signal carrying a data stream representativeof an image or a sequence of images, said stream including datarepresentative of pixel groups, referred to as blocks, in one of saidimages, wherein: said stream further includes data representative of adata structure associated with a set of said blocks referred to as acluster of blocks, said structure including at least data representativeof a characteristic value of said cluster of blocks and corresponding toa block coding parameter; and the data representative of a block of saidcluster either contains no data representing a value of said codingparameter or contains data representative of a refinement of saidcharacteristic value.
 9. A device for coding an image or a sequence ofimages generating a data stream including data representative of pixelgroups, referred to as blocks, in one of said images, the deviceincluding: means for grouping blocks into a cluster of blocks accordingto the proximity of their respective values corresponding to at leastone block parameter to be coded; means for determining a characteristicvalue of said cluster of blocks for said parameter to be coded; meansfor coding a data structure associated with said cluster of blocks, saiddata structure including data associated with said characteristic value;and means for coding blocks of said cluster, including at least one of:means for implicitly coding values of said blocks for said parameter byinheritance of said characteristic value; and/or means for coding saidvalues as refinements of said characteristic value.
 10. A device fordecoding a data stream representing an image or a sequence of images,said stream including data representative of pixel groups, referred toas blocks, in one of said images, the device comprising: means fordecoding a data structure associated with a set referred to as a clusterof said blocks and at least one characteristic value of said cluster ofblocks corresponding to a block coding parameter; and means for decodinga block of said cluster, assigning to said coding parameter either saidcharacteristic value if said parameter is not coded for said block or arefinement value of said characteristic value calculated from the valuecorresponding to said coded parameter if said parameter is coded forsaid block.
 11. A computer program including instructions for executinga method of coding an image or a sequence of images generating a datastream that include data representative of pixel groups, referred to asblocks, in one of said images, when the method is executed on acomputer, wherein the method comprises: grouping blocks in a cluster ofblocks according to proximity of their respective values correspondingto at least one block parameter to be coded; determining a value of saidparameter, said value being characteristic of said group of blocks; andcoding blocks of said cluster, where the values of said blocks for saidparameter are coded implicitly by inheritance of said characteristicvalue or are coded as refinements relative to said characteristic value,and coding a data structure associated with said cluster of blocks, saiddata structure including data associated with said characteristic value.